Deploying Agents: 7 Essential Steps
I've been there—agents deployed, costs soaring, chaos ensues. Sometimes, it's like watching an agent run up a 10k bill overnight. Let's talk about the seven key things you need to lock down before any agent hits production. In this article, I walk you through my workflow and the lessons learned. We'll discuss model control, setting up guardrails, and how to prevent your agents from hallucinating for 200 different users.

I've been there—agents deployed, costs soaring, chaos ensues. Picture an agent running up a 10k bill overnight—it's happened to me. Before any agent hits production, there are seven essential steps you need locked down. First off, model control is key. Without it, your agents might end up hallucinating for 200 different users. Then, you need to orchestrate prompts and set up guardrails. You don't want your agents going rogue. And finally, cost management is critical—nothing like an unexpected bill to stress the importance of setting budget limits. I'll walk you through my workflow, the mistakes I've made, and how I learned to centralize authentication and manage tools. So, let's dive in!
Model Control and Prompt Management
First, I ensure model control is tight—it's your intellectual property, protect it. I've gotten burned by not having a unified layer between my code and models. Imagine your go-to model gets deprecated overnight. You need the flexibility to swap models in and out without rewriting everything. Never hard-code model names, especially with updates flying in monthly.

Then, prompt management isn't just a task; it's a strategy for consistency. Watch out for prompt drift, it can derail your agent's performance. Use a prompt registry to keep track of changes and versions. It's not just a luxury, it's a necessity.
- Protect your intellectual property
- Prevent prompt drift
- Use a prompt registry
Setting Up Guardrails for Safety
Guardrails are non-negotiable; they protect inputs and outputs. I implement input validation to prevent rogue requests. I've seen agents run wild, racking up $10k overnight. Output filtering is crucial too, given that agents can "hallucinate." But watch out, too many guardrails can stifle creativity. Balance is key.
I've witnessed scenarios where agents hallucinated for 200 different users in a single day. It underscores the importance of robust guardrails.
- Implement input validation
- Filter outputs to prevent "hallucinations"
- Find the balance between safety and creativity
Budget Limiting to Prevent Overruns
I set budget limits early, having seen $10k bills appear overnight. Use cloud service tools to monitor and cap spending. Consider tiered budgeting based on usage patterns. Sometimes, it's faster to manually intervene than automate everything.

Manual intervention can sometimes prevent a financial disaster. I've seen finance teams go through what I call "the AI cost awakening." They think they have it covered with a 20% buffer, but often end up surprised.
- Set budget limits early
- Use spending monitoring tools
- Be ready to intervene manually if necessary
Centralizing Authentication and Tool Management
Centralized authentication simplifies tool access. MCP servers can streamline this process—I've seen it cut setup time significantly. Ensure all tools are compliant with your security protocols. Centralization reduces errors and increases efficiency.
By centralizing, you limit human error and gain efficiency. This is a lesson I learned after seeing API keys leak into the wild.
- Simplify access with centralized authentication
- Use MCP servers to streamline the process
- Ensure tool compliance
Monitoring and Evaluating System Performance
OpenTelemetry is my go-to for tracing and monitoring. Evaluate system performance regularly; don't wait for failures. Set up alerts for anomalies—200 users hallucinating isn’t something you forget.

It's about balancing monitoring depth with resource usage. Over-monitoring can be costly.
- Use OpenTelemetry for monitoring
- Evaluate performance regularly
- Avoid costly over-monitoring
First, I ensure my agents are orchestrated with well-defined controls. Without this, I've had rogue agents run up a 10k bill overnight too many times. Next, I rigorously manage prompts and model control so my agents don't start hallucinating for 200 different users. But watch out, centralizing authentication is key to avoid chaos in tool management. Finally, I set clear budget limits to prevent unexpected expenses. These steps are a real game changer for deploying agents effectively. Ready to deploy smarter? Start implementing these strategies today and watch your agents perform without the chaos. For practical insights and tips, check out the '7 Things For Agents in Production' video on YouTube. Trust me, it's worth the watch.
Frequently Asked Questions

Thibault Le Balier
Co-fondateur & CTO
Coming from the tech startup ecosystem, Thibault has developed expertise in AI solution architecture that he now puts at the service of large companies (Atos, BNP Paribas, beta.gouv). He works on two axes: mastering AI deployments (local LLMs, MCP security) and optimizing inference costs (offloading, compression, token management).
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